Ethan Goan

Ethan Goan is a Research Fellow at Queensland University of Technology (QUT) within the Faculty of Engineering, specifically affiliated with the School of Electrical Engineering & Robotics. He is actively involved with the Centre for Data Science and specializes in Signal Processing, Artificial Intelligence, and Vision Technologies research areas.

His educational background includes:

• PhD pending conferral (as of February 27, 2024) from Queensland University of Technology
• Bachelor of Engineering (Electrical) from Queensland University of Technology

Dr. Goan's research focuses on the intersection of artificial intelligence and signal processing, with particular expertise in Bayesian neural networks and their applications. His work spans multiple domains including medical imaging, radar signal processing, computer vision, and digital health. His recent publications demonstrate strong emphasis on uncertainty quantification in deep learning models, particularly for real-time applications on embedded systems. His research combines theoretical advances in probabilistic modeling with practical applications across healthcare, robotics, and signal processing domains.

His publication record shows consistent output since 2016, with increasing focus on deep learning approaches to solve complex problems in signal processing and computer vision. Recent work demonstrates expertise in zero-shot learning frameworks, semantic segmentation, and the application of AI to medical diagnostics and digital health monitoring.

Dr. Goan collaborates extensively with researchers across multiple institutions, as evidenced by his co-authorship on large-scale collaborative projects such as the Parkinson's Disease Digital Biomarker DREAM Challenge. His work appears in prestigious venues including IEEE conferences, Nature partner journals, and specialized machine learning publications.

He is affiliated with the Centre for Data Science at QUT and works within the Signal Processing, Artificial Intelligence and Vision Technologies research group, contributing to QUT's growing reputation in AI and robotics research.